Bioimage Informatics for Big Data.

Journal: Advances in anatomy, embryology, and cell biology
Published Date: Jan 1, 2016

Abstract

Bioimage informatics is a field wherein high-throughput image informatics methods are used to solve challenging scientific problems related to biology and medicine. When the image datasets become larger and more complicated, many conventional image analysis approaches are no longer applicable. Here, we discuss two critical challenges of large-scale bioimage informatics applications, namely, data accessibility and adaptive data analysis. We highlight case studies to show that these challenges can be tackled based on distributed image computing as well as machine learning of image examples in a multidimensional environment.

Authors

  • Hanchuan Peng
    New Cornerstone Science Laboratory, SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu 210096, China.
  • Jie Zhou
    Departments of Ultrasound, Jiading District Central Hospital Affiliated Shanghai University of Medicine &Health Sciences, Shanghai, China.
  • Zhi Zhou
    Department of Neurology, China-Japan Friendship Hospital, Beijing, China.
  • Alessandro Bria
    Department of Engineering, University Campus Bio-Medico of Rome, Rome, Italy.
  • Yujie Li
    College of Orthopedics and Traumatology, Henan University of Chinese Medicine, Zhengzhou, China.
  • Dean Mark Kleissas
    Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
  • Nathan G Drenkow
    Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA.
  • Brian Long
    Allen Institute for Brain Science, Seattle, WA, USA.
  • Xiaoxiao Liu
    Allen Institute for Brain Science, Seattle, WA, USA.
  • Hanbo Chen
    Allen Institute for Brain Science, Seattle, WA, USA. cojoc.chen@gmail.com.

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